数字图像语义标注框架的开发与应用

Jinju Chen, Shiyan Ou
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引用次数: 0

摘要

目的利用语义网技术对数字图像的内容进行语义标注,从而方便检索、整合和知识发现。设计/方法/方法在对现有图像语义标注模型进行回顾和比较的基础上,深入分析了图像内容的特点,提出了一种多维层次的数字图像通用语义标注框架。在此基础上,以历史图像、广告图像和生物医学图像为例,通过将这些特定领域的图像特征与相关领域知识相结合,定制数字图像通用语义标注框架,形成特定领域图像的领域标注本体。探讨了数字图像语义标注在语义检索、可视化分析和语义重用等方面的应用。结果表明,本文构建的数字图像语义标注框架为图像内容的语义组织提供了一种解决方案。在此基础上,可以提供语义检索、可视化分析等深度知识服务。独创性/价值数字图像语义标注框架能够多维、分层地揭示细粒度语义,从而满足数字图像丰富和检索的需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development and application of the semantic annotation framework for digital images
Purpose The purpose of this paper is to semantically annotate the content of digital images with the use of Semantic Web technologies and thus facilitate retrieval, integration and knowledge discovery. Design/Methodology/Approach After a review and comparison of the existing semantic annotation models for images and a deep analysis of the characteristics of the content of images, a multi-dimensional and hierarchical general semantic annotation framework for digital images was proposed. On this basis, taking histories images, advertising images and biomedical images as examples, by integrating the characteristics of images in these specific domains with related domain knowledge, the general semantic annotation framework for digital images was customized to form a domain annotation ontology for the images in a specific domain. The application of semantic annotation of digital images, such as semantic retrieval, visual analysis and semantic reuse, were also explored. Findings The results showed that the semantic annotation framework for digital images constructed in this paper provided a solution for the semantic organization of the content of images. On this basis, deep knowledge services such as semantic retrieval, visual analysis can be provided. Originality/Value The semantic annotation framework for digital images can reveal the fine-grained semantics in a multi-dimensional and hierarchical way, which can thus meet the demand for enrichment and retrieval of digital images.
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